journal of pediatric oncology nursing 2010 demmel 229 40

http://jpo.sagepub.com/Nursing

Journal of Pediatric Oncology

http://jpo.sagepub.com/content/27/4/229The online version of this article can be found at:

DOI: 10.1177/1043454209358410

2010 27: 229 originally published online 26 February 2010Journal of Pediatric Oncology NursingKathleen M. Demmel, Lucinda Williams and Laura Flesch

UnitImplementation of the Pediatric Early Warning Scoring System on a Pediatric Hematology/Oncology

Published by:

http://www.sagepublications.com

On behalf of:

Association of Pediatric Hematology/Oncology Nurses (APHON)

can be found at:Journal of Pediatric Oncology NursingAdditional services and information for

http://jpo.sagepub.com/cgi/alertsEmail Alerts:

http://jpo.sagepub.com/subscriptionsSubscriptions:

http://www.sagepub.com/journalsReprints.navReprints:

http://www.sagepub.com/journalsPermissions.navPermissions:

http://jpo.sagepub.com/content/27/4/229.refs.htmlCitations:

What is This?

- Feb 26, 2010 OnlineFirst Version of Record

- Jun 18, 2010Version of Record >>

at SAMUEL MERRITT UNIV on May 21, 2013jpo.sagepub.comDownloaded from

http://jpo.sagepub.com/

http://jpo.sagepub.com/content/27/4/229

http://www.sagepublications.com

http://www.apon.org

http://jpo.sagepub.com/cgi/alerts

http://jpo.sagepub.com/subscriptions

http://www.sagepub.com/journalsReprints.nav

http://www.sagepub.com/journalsPermissions.nav

http://jpo.sagepub.com/content/27/4/229.refs.html

http://jpo.sagepub.com/content/27/4/229.full.pdf

http://jpo.sagepub.com/content/early/2010/02/26/1043454209358410.full.pdf

http://online.sagepub.com/site/sphelp/vorhelp.xhtml


Journal of Pediatric Oncology Nursing27(4) 229 –240© 2010 by Association of Pediatric Hematology/Oncology NursesReprints and permission: sagepub.com/journalsPermissions.navDOI: 10.1177/1043454209358410http://jopon.sagepub.com

Implementation of the Pediatric Early Warning Scoring System on a Pediatric Hematology/Oncology Unit

Kathleen M. Demmel, MHA, RN,1 Lucinda Williams, MSN, RN, PNP,2 and Laura Flesch, RN, MSN, CFNP1

Abstract

Despite improved outcomes for pediatric Hematology/Oncology patients over the past 15-20 years, sepsis and other acute events continue to cause serious illness in these children. Implementing a pediatric early warning scoring tool (PEWS) with an associated multi-disciplinary action algorithm in a pediatric Hematology/Oncology unit helped to remove barriers that prevented timely referral of children who are clinically deteriorating and requiring immediate help, enhanced multi-disciplinary team communication, and has led to a more than 3-fold increase in days between codes on the Hematology/Oncology unit.

Keywords

pediatric deterioration, PEWS, failure to rescue

IntroductionFollowing the initial Institute of Medicine (IOM) report in 1999 To Err is Human: Building a Safer Health System, the U.S. health care system and the public were shocked by the conclusion that our health care system was not as safe as health care providers and the public previously believed and desired. Intense efforts at the local, state, and national levels followed this report and continue to be directed at creating safer health care environments for patients. In 2004, the Institute for Healthcare Improve-ment launched the 100,000 Lives Campaign and most recently the 5 Million Lives Campaign. The 100,000 Lives Campaign was endorsed by the American Nurses Association, the Centers for Medicare and Medicaid Services, the American Medical Association, the Joint Commission on Accreditation of Healthcare Organiza-tions, the Association of American Medical Colleges, the Agency for Healthcare Research and Quality, and other quality improvement organizations and state hospital asso-ciations (Gosfield & Reinertsen, 2005). Subsequently, thousands of hospitals have launched patient safety initiatives (Institute for Healthcare Improvement, 2005).

In 2005, the U.S. Congress mandated that U.S. hospi-tals develop a culture of safety, and President Bush signed into law the Patient Safety and Quality Act (Mattie, 2007). The Agency for Healthcare Research and Quality developed national patient safety indicators. Failure-to-rescue was one of those indicators. Failure-to-rescue is

defined as deaths resulting from a complication rather than the primary diagnosis. In-hospital cardiopulmonary arrests occurring outside the intensive care unit (ICU) represent failure-to-rescue events (Agency for Health-care Research and Quality, 2004). Recognition of the failure to identify and rescue adults who were clinically deteriorating in hospital units led to the implementation of interventions such as early-warning scoring systems and rapid response teams (Buist, Jarmolowski, et al., 1999; Goldhill, Worthington, Mulcahy, Tarling, & Sumner, 1999; McGloin, Adam, & Singer, 1999; McQuil-lan et al., 1998). In addition, the underlying premise of IOM’s initial campaign in 2004 included 6 evidence-based, proven interventions and suggested that if these were reliably implemented in U.S. hospitals, 100,000 hospital deaths would be prevented over the first 18 months of the campaign, and every year following. One of those inter-ventions included a system of rapid response teams to immediately bring skilled resources to the bedside of any patient who was rapidly deteriorating (Gosfield & Reinertsen, 2005). The Joint Commission included the

1Cincinnati Children’s Hospital, Cincinnati, OH, USA2Children’s Hospital Boston, Boston, MA, USA

Corresponding Author:Lucinda Williams, MSN, RN, PNP, Children’s Hospital Boston, 300 Longwood Avenue, Boston, MA 02115, USAEmail: [email protected]



230 Journal of Pediatric Oncology Nursing 27(4)

improvement of the recognition and response to changes in a patient’s condition as one of the 2009 National Patient Safety Goals for Hospitals and Critical Access Hospitals (Joint Commission on Accreditation of Health-care Organizations, 2009). Getting the patient the right care, at the right time, and in the right place is essential to ensuring safe care (Greaves, Porter, & Ryan, 2001).

There are reports that 8.5% to 14% of all in-hospital cardiopulmonary arrests in children occur outside the ICU, and the mortality rate for these patients is 50% to 67% (Lopez-Herce et al., 2004; Nadkarni et al., 2006; Reis, Nadkarni, Perondi, Grisi, & Berg, 2002; Suominen et al., 2000). This high mortality rate in children makes early identification of hospitalized children clinically deteriorating outside the ICU particularly important. It has been suggested that patient acuity scoring tools can serve to complement clinicians’ expertise in achieving that outcome (Duncan, Hutchison, & Parshuram, 2006; Tume, 2007).

In the adult literature, there is growing evidence that early warning scoring tools and rapid response teams are effective interventions when a patient’s condition deteriorates (Ball, Kirkby, & Williams, 2003; Priestley et al., 2004). Recently, pediatric health care providers have been learning from the adult experience. Early-warning scoring tools developed specifically for children are important because the anatomy and physi-ology of children differ from adults and changes throughout childhood (Patel, 2008). Ideally, triage tools should be quick, valid, reproducible, and strongly pre-dictive of clinical outcomes (Maningas, Hime, & Parker, 2006; O’Cathain, Webber, Nicholl, Munro, & Knowles, 2003).

Risk of Clinical Deterioration in Pediatric Hematology/Oncology PatientsOver the past 15 to 20 years, advances in the knowledge of pediatric hematology/oncology and improvements in therapy have led to improved patient outcomes. In many cases, improvements have been dramatic and substan-tially reduced morbidity and mortality (Fiser et al., 2005; Mendes, Sapolnik, & Mendonca, 2007; National Cancer Institute, 2006). However, sepsis and other acute events continue to cause serious illness in these children. Blood stream infections are a common cause of morbidity and mortality in pediatric oncology patients, which most often is the result of treatment-associated immunosuppression (Mendes et al., 2007; Tamburro, 2005). There is an increased incidence of sepsis in children with leukemia and lymphoma when compared with children with solid tumors. The mortality rate is higher in children having undergone bone marrow transplant (Hallahan et al., 2000; Mendes et al., 2007).

Sepsis causes death in 10% of the general pediatric population, and in children with cancer this increases to 16% (Mendes et al., 2007). The early recognition and treat-ment of sepsis is crucial to the early reversal of shock, which results in improved outcomes (Han, Carcillo, & Dragotta, 2000). The signs and symptoms of clinical decompensation in children may be variable and non-specific and can go unrecognized. This is particularly true of sepsis in neonates (Gerdes, 1991; Verboon-Maciolek et al., 2006).

Rapid Response TeamsRapid response teams (RRTs) are endorsed by the Institute for Healthcare Improvement as a mechanism to prevent deaths and reduce complications in patients who are fail-ing outside ICUs (Institute for Healthcare Improvement, 2005). RRTs consist of clinicians who have been trained to recognize signs of respiratory or cardiopulmonary failure prior to full arrest. The configuration of the team varies by institution and may include any or all of the following: a critical care practitioner (physician or nurse practitioner), an ICU nurse, and a respiratory therapist. The goal of the RRT is to bring critical care expertise and skill to the bedside of a clinically deteriorating patient who is not in the ICU. One study found that RRTs were effec-tive in preventing codes outside the ICU and decreased the mortality rate of pediatric patients by 18% (Sharek et al., 2007). The RRT can only be effective if called to the patient’s bedside in adequate time, making early recogni-tion of clinical deterioration vital.

In 2005, the Institute for Healthcare Improvement cited a chart review that revealed that 73% of pediatric cardiopulmonary arrests had detectable antecedents, and in another article, it was reported that there were detect-able clinical antecedents as long as 18 hours prior to arrest (Sharek et al., 2007). As nurses are at the bedside around the clock, the responsibility often resides with them for timely assessment, accurate interpretation, and synthesis of physiological findings and the activation of an RRT, or similar system. Nurses provide clinical reasoning and decision making, which are integral to quality health care and have a large impact on the health care system’s “safety net” (Moorhead, Johnson, Maas, & Swanson, 2008).

The Importance of Standardized Nursing Assessment ToolsThe management of critically ill patients is variable between shifts and depends entirely on the skills, experience, and judgment of the staff members on duty, leading to a poorly standardized approach (Buist, Moore, et al., 2002). Stan-dardized nursing assessment tools that link physiologic



Demmel et al. 231

parameters with specific nursing actions such as the pedi-atric early warning scoring system (PEWS) may improve the early identification and rescue of patients who are clinically deteriorating on units outside the ICU by employ-ing a consistent assessment tool used by all nurses, regardless of experience.

History and the Development of the Pediatric Early Warning Scoring SystemThe PEWS tool and associated scoring process was initially developed at the Royal Alexandra Children’s Hospital and Sussex University Hospitals NHS (Monaghan, 2005). The work was based on the premise that the early detection of children at risk for clinical deterioration would ultimately improve patient outcomes through early intervention, as previously demonstrated with the adult population (Department of Health, 2002). The PEWS was the first severity of illness score developed for children admitted to hospital units. Prior to this time, adult-focused risk deterioration identification processes had been used.

The PEWS identifies objective pediatric patient assess-ment criteria centered on behavior, color/cardiovascular status, and respiratory status (Monaghan, 2005; see Figure 1). The score was designed for nursing staff to be able to identify patients with at least a 1-hour warning before a cardiopulmonary arrest. This would allow time to initiate unit-based patient management and arrange trans-fer to a higher acuity patient care unit, if indicated.

Parameters centering on behavior (i.e., playing/appropri-ate behavior, sleeping; irritable, lethargic/confused, or reduced response to pain; see Figure 1) were established because behavioral changes are often associated with ini-tial signs of shock and easily recognized by parents. Patient color and capillary refill were selected as cardio-vascular measures. Respiratory rate along with oxygen requirements (defined as liters per minute) comprised the respiratory measures (Monaghan, 2005).

The PEWS Scoring ProcessThe scoring process entails assigning a criteria-based numerical value to the patient’s behavioral, cardiac, and respiratory status, ideally through the routine course of nursing assessments using the PEWS grid and normal vital sign parameters as determined by each individual institu-tion. Pediatric patients are scored every 4 hours according to physiologic and behavioral parameters (see Figure 1).

The score, ranging from 0 to 9, identifies those children with deteriorating clinical status and classifies the type of care a child requires (see Figure 1). A higher score indicates a worse clinical condition. There are graduated interventions for patients scoring at various thresholds according to an algorithm (Figure 2). A score of 0 to 2 means the child is stable and calls for ongoing routine monitoring; 3 to 5 means the child is at risk of clinical deterioration and requires more frequent assessment and attention from the health care team. A score of 7 to 9 warrants evaluation

Figure 1. Pediatric early warning score




Figure 2. Watchful eye algorithm “Pediatric early warning score”



Demmel et al. 233

by the RRT. These steps can easily be adapted and modified by individual pediatric institutions according to available resources and specific circumstances within those institu-tions (Monaghan, 2005).

Institutional Decision to Implement PEWSIn 2001, the hematology/oncology/bone marrow trans-plant programs at Cincinnati Children’s Hospital Medical Center (CCHMC) were growing at the same time that the institution made a major commitment to improving patient safety. An institutional comprehensive patient safety pro-gram was developed whose purpose was to identify, evaluate, reduce, respond to, and prevent harm to patients throughout the organization. One of CCHMC’s Patient Safety Program’s initiatives included reducing and/or elim-inating preventable codes outside the ICU; one of the initial 6 focuses of the Institute for Healthcare Improvement 100,000 Lives Campaign (Gosfield & Reinertsen, 2005).

The PEWS was initially trialed at CCHMC on a general medical unit. Once the test unit demonstrated improved patient outcomes following PEWS implementation and the algorithm was evaluated and refined, the initiative moved to other units throughout the hospital.

Successful PEWS Implementation on a Hematology/Oncology UnitThe hematology/oncology/bone marrow transplant nurs-ing and medical leadership team decided to implement

the PEWS initiative after reviewing the pilot results, reviewing related medical literature, and observing the institutional and national focus on improvements in patient safety.

Implementation GoalsThe anticipated outcome of introducing PEWS was not only the prevention of unit cardiopulmonary arrests but also to provide a clear standardized assessment process by which to alert a large multidisciplinary care team with varying levels of experience to the signs of clinical dete-rioration. Additional team goals for the implementation included early identification of children who are clinically deteriorating outside the ICU, enhanced understanding of triggers of clinical deterioration that would signal the need for further assessment and possible intervention, empow-erment of the nursing staff to call for assistance, and development of predictable responses by all levels and members of the interdisciplinary team according to an algorithm linked to the PEWS score.

Development of an ActionAlgorithm Based on PEWS ScoresThe PEWS tool in and of itself cannot guarantee that the appropriate action will be taken. Subsequent intervention is necessary. In a series of in-hospital cardiac arrests, clin-ical deterioration had been documented in 66% of patients. Where there was documentation of clinical deterioration and the patient progressed to cardiopulmonary arrest, the

0.6

0.9

1.0

0.9 0.9 0.9

1.0

0.90.9

1.00.9

1.0 1.0 1.01.0

1.0

0

1

7.23.0

7

9.17.0

7

10.30

.07

11.6.

07

11.13

.07

12.3.

07

12.10

.07

1.27.0

8

3.17.0

8

4.7.08

4.15.0

8

4.23.0

8

4.29.0

8

5.7.08

5.20.0

8

5.26.0

8

Week of

Per

cen

tag

e o

f C

om

plia

nt

Sco

res

Scoring Compliance Median Centerline

0.2

0.4

0.6

0.8

Figure 3. A5S PEWS scoring compliance through May 26, 2008




To ensure that escalating proper actions were taken, an associated multidisciplinary algorithm was developed that defined specific care responses to be implemented by all members of the multidisciplinary team according to the child’s PEWS score (see Figure 2). This minimized dependence on the level of experience and workload of individual team members. It has been reported that matching the score to an algorithm aids clinical decision making (Monaghan, 2005).

ImplementationFormation of a multidisciplinary team was the first step. The PEWS team included staff nurses, educators, charge nurses, residents, oncologists, a hematologist, unit nurs-ing leadership, performance improvement facilitators, and an ICU staff member and leadership staff from the unit where PEWS was initially implemented at CCHMC. The initial PEWS implementation was planned for the hematology/oncology unit, and subsequent implementa-tion for the more complex and acutely ill blood and

PEWS is based on normal vital sign parameters

Respiratory Rateat rest

Heart Rateat rest

16-1855-90Adolescent (13 -19 years)

19-2170-110School Age (7-12 years)

21-2370-110Preschool (4-6 years)

25-3070-110Toddler (13 months-3 years)

35-40100-180 Infant (1-12 months)

40-60100-180Newborn (birth-1 month)

Normal Parameters

Hockenberry, M.J., Wilson, D., & Winkelstein, M.L. (2005). Wong’sessentials of pediatric

nursing. 7th ed. Elsevier Mosby: St Louis.

Figure 4. PEWS is based on normal vital sign parameters

18 0

3181

32 64

1522

32 320

500

1000

1500

2000

2500

3000

3500

Score of 0-2 Score of 3 Score of 4+

Nu

mb

er o

f S

core

s

Scoring Categories

Hematology Pts Oncology Pts BMT Pts

Figure 5. Initial PEWS scoring breakdown by patient type

nurse did not inform the doctor, junior doctors did not inform senior doctors, or intensive care doctors did not follow usual procedures (Franklin & Mathew, 1994).



Demmel et al. 235

marrow transplant population was planned for a later time once the process was well established on the hema-tology/oncology unit (see Figures 3-5).

Historical data were collected pertaining to unplanned ICU transfers from the oncology unit, changes in patients’ clinical status, frequency of calls to the RRT, and prevent-able code rates. These data would serve as a baseline, which could be compared with postimplementation findings.

The plan for introducing the PEWS and the associated algorithm was divided into a series of smaller steps with specific project aims. The planning team defined and pri-oritized project aims, identified the key drivers of each specific aim, and designed interventions directed at the aim with an associated timeline (Figures 6 and 7). Rapid Plan-Do-Study-Act (PDSA) cycles were implemented using small tests of change. The data from the PDSA cycles were continuously collected, analyzed, and reviewed with the multidisciplinary staff and planning team and used to give ongoing direction to the implementation plan.

Preimplementation Staff EducationEarly staff education focused on the history and devel-opment of PEWS along with the rationale for and the

goals of the initiative. The scoring process was explained and how it would be integrated into routine nursing assessments; normal vital sign parameters were reviewed. CCHMC chose Wong’s Essentials of Pediatric Nursing, 7th edition, as the reference for vital sign parameters (see Figure 4). The staff practiced applying the scoring in interactive case scenarios. Reviewing case histories involving patients that the staff had previously cared for proved to be engaging and an effective teaching strategy.

In preparation for the implementation of PEWS, a large white board was posted in a highly visible location on the unit and nursing staff then began to score patients every 4 hours based on the PEWS scoring tool to estab-lish baseline scores of our unit’s stable and acutely ill population (see Figure 8). The scoring data were captured electronically from the documentation of nursing’s patient assessments. Data retrieval was supported by the hospital’s information systems department.

Establishing Baseline Scoring TrendsNursing staff scored patients at intervals of every 4 hours for 1 month. The PEWS implementation team analyzed

By December 31, 2007,100% of A5S nursing

Staff will have adoptedPEWS scoring tool

Key DriversDesign Changes

Aim

Education

DATA COLLECTION

ALGORITHM REFINEMENT

Educational Approaches• Classroom presentations• Self study Module

Data Collection• Tracking calls to physicians• Tracking ICU admissions and accompanying patient clinical picture/condition along with PEWS Scores and scoring frequency• ICIS PEWS Scoring and Algorithm link

Collaboration• Team intradisciplinary in nature• A5 specific algorithm development and refinement by all team members

Figure 6. Learning structure




the data and reviewed the data for any patients that were transferred to the ICU for clinical deterioration.

Initial PEWS data were sorted according to each numerical score in order to determine scoring frequency for each scoring result allowing for determination of overall unit acuity and scoring patterns (see Figure 5). Scores of patients transferred to the ICU were retrospec-tively examined for the 5 to 24 hours prior to transfer (depending on length of time on the unit) in order to assure that the scoring process appropriately reflected the patients’ increasing acuity prior to ICU transfer. The 3 patients transferred to the ICU demonstrated scores of 5 or above within 3 hours of ICU transfer. One patient maintained scores of 5 and above for 7 hours prior to transfer; the other patient, who was an emergency room transfer, maintained scores of 5 and above for the 3 hours on the unit prior to ICU transfer.

Staff members were surprised at the baseline scoring results because many thought the baseline scores would be much higher given the patient population complexity and acuity. With scoring trends identified, the team designed the hematology/oncology patient population

algorithm, which specified graduated actions of various team members according to the PEWS score (Figure 2).

Continued Staff Education and Activation of Scoring and Algorithm ImplementationAdditional staff education followed. Presentations were developed that focused on the PEWS scoring process, application of the score to the algorithm, and the execu-tion of the prescribed action. Case studies ended the session allowing for scoring practice and algorithm use. Education was presented at staff meetings and made available to all staff electronically.

The PEWS Scoring Tool, the normal vital sign parameters, and the hematology/oncology algorithm were distributed to all staff members and posted throughout the unit at strategic locations, including computer and nursing stations. The visual aids were also made available elec-tronically on the unit’s Web site so that all staff had easy access to the information. The algorithm initially appeared visually “busy” and complicated, but the staff found the algorithm implementation easy and intuitive

PEWS Scoring on HEM/ONC

Objective Full implement of the PEWS Scoring System on A5South by Decem

Population A5 South Staff and patients

TEST CYCLE 1 Start Date: 7/11/07 End Date: 7/23/07

Plan & Prediction PLAN: To educate A5South nursing staff about the PEWS Scoring process so prepared to initiate scoring on7/23/07. PREDICTION: Staff will be trained and will be prepared to initiate scoring process on 7/23/07.

Do Staff participated in learning via educational sessions and self learning module. It is an ongoing challenge toreach 69 staff members working a variety of shifts and get all trained in a short period of time.

Study The majority of staff members were trained prior to the implementation of PEWS. Having the self learningmodule available made study completion much especially for those working off shifts and weekends. In future,whenever possible more training lead time is preferable.

Act Future training will be made available via classroom and self learning modules. PEWS Scoring to begin 7/23/07.Educators are working with staff members who have not completed training on an individual basis.

TEST CYCLE 2 Start Date: 9/01/07 End Date: 9/08/07

Plan & Prediction Plan: To continue PEWS scoring on all A5S patients, record score on patient board, PCF tabulate scoring databy completion of each shift PREDICTION: Less labor intense data collection and greater PEWS scoring compliance.

Do

Study

Act

Figure 7. Tests of change



Demmel et al. 237

(Figure 2). With the initial education complete, the hema-tology/oncology PEWS algorithm was activated and full scoring and multidisciplinary action steps according to the algorithm were implemented.

Nursing staff began posting each patient’s score on the unit’s PEWS Score Board, a laminated grid that includes room number and each hour within a 24-hour period. Each child’s PEWS score was indicated by drawing a colored circle on the board at the correspond-ing room number and hour of day the score was obtained. The color corresponds with the color associ-ated with the patient’s score on the algorithm. If a patient scored a “3” for example, the circle on the board would be green. The PEWS white board is located in a highly visible area on the unit, providing the multidis-ciplinary team with a dynamic snapshot of the unit’s acuity level and view of the sickest patients at any given time (Figure 8).

Ongoing Monitoring, Evaluation, and Education

Once the algorithm was activated, there was ongoing review of patient scores and staff actions in response to the scores in order to evaluate staff members” ability to score accurately, consistently, and follow the algorithm (Figure 3). Initially, weekly scoring and algorithm com-pliance were monitored to ensure interrater reliability by having 2 nurses independently score selected patients and comparing their PEWS score results. Consistent scoring among staff members improved over time (Figure 9). ICU transfers and associated PEWS scoring trends were also reviewed in order to evaluate the appropriateness of algorithm actions.

Periodic PEWS Implementation Team meetings fol-lowed, and the compiled data were reviewed to ensure a sound algorithm design. Since its inception in September 2007, the algorithm has undergone 3 revisions. Each refinement was based on both reviewed data and feed-back from all care team members.

Creating an Exception AlgorithmThe multidisciplinary team’s development and use of an “exception algorithm” was effective and efficient in man-aging patients with chronic conditions, such as anemia, that can lead to persistent elevated PEWS scores in chil-dren that were hemodynamically stable.

The exception algorithm allows the care team to design a patient-specific plan of care when a child has 3 con-secutive scores of 5 or above but is considered medically

Figure 8. A5S “watchful eye”

Figure 9. A5S PEWS scoring accuracy through 5/26/08

Figure 10. Nursing staff satisfaction with PEWS implementation




stable. The patient-specific plan is reevaluated at least every 24 hours. The exception algorithm tailors interven-tions to the particular child’s situation. The plan may be as general as calling the physician if the patient scores one level higher or as specific as to call if heart rate increases by a determined rate and/or the child is not able to main-tain oxygen saturation above a predetermined level such as 90%.

Staff Evaluation of the PEWS ImplementationNursing staff and house officers were surveyed to gather their feedback and level of satisfaction about using PEWS and its impact on patient care. There was a 29% response rate from the nursing staff and a 36% response rate from the residents that were surveyed. The feedback from the staff that responded to the survey was primarily positive (Figures 10 and 11), citing that the PEWS scoring process improved communication among multidisciplinary team members and defined clear actions for new, less experienced staff members to address patient clinical deterioration. For patients that had the potential for rapid deterioration, elevated PEWS scores facilitated the timely arrival of appropriate staff to the bedside for further evaluation and intervention.

Staff and the charge nurses found it helpful to glance at the board throughout the shift and determine if another staff member might need assistance with their patient assignment. Because the Implementation Team could not be on the unit around the clock and 7 days a week, a high level of charge nurse involvement helped keep the initia-tive “alive” shift-to-shift and on weekends. Positive feedback from the multidisciplinary team about instantly being able to determine which patients were most ill by viewing the PEWS scoring board served as early valida-tion of the benefits of the initiative.

Lessons Learned

Implementing the PEWS tool alone does not guarantee that the appropriate action will be taken when a child is clinically deteriorating. Developing and implementing an algorithm that linked specific multidisciplinary care responses to each score allowed all team members to predict responses expected of various colleagues. This algorithm defined the threshold for caregiver time to response and the seniority and expertise of personnel to be contacted.

On several occasions when there was reluctance on the part of a team member to act on a particular patient’s PEWS score, nursing staff found it helpful to refer to the algorithm that defined the expected response.

The system removed barriers that prevented the timely referral of children who are clinically deteriorat-ing and require immediate help. Although cardiopulmonary arrest preimplementation of PEWS was a relatively rare event on the hematology/oncology unit, the days between codes has improved since implementation. Immediately prior to implementation of PEWS, the number of days between cardiopulmonary arrests on the unit was 299. Postimplementation, the days between cardiopulmonary arrests on the unit has increased to 1,053 and has been sustained at that level for nearly 2 years. PEWS data have assisted in quantifying patient acuity and the develop-ment of criteria for nurse staffing adjustments that allows data-driven staffing responses to the dynamic nature of patient acuity.

A less desirable aspect of the implementation, according to the nursing staff, is that scoring a minimum of every 4 hours could be mundane and monotonous for patients that had lower PEWS scores. Even with the assistance of the hospital’s information systems department, ongoing data management can be cumbersome and time consum-ing. We found that careful, thoughtful determination of essential data that must be tracked is an important time saving approach and that the appropriate resource alloca-tion such as support of IT personnel was important to plan preimplementation.

In an attempt to develop robust outcome measures, the team explored the potential of tracking precursory events independent of PEWS scoring parameters such as blood gas values and fluid bolus administration. However, the tracking of these additional parameters has proved too burdensome to sustain. Until alternatives are developed, the team will continue to rely on the outcome measure “days between preventable codes.”

In the future, the inclusion of additional scoring parameters including blood pressure may enhance the utility of the PEWS scoring process in pediatric patients. Adapting and refining the algorithm for specific popula-tions of patients may prove to further enhance PEWS

Figure 11. Resident’s satisfaction with PEWS implementation



Demmel et al. 239

value, as well. Further work on the validation of the PEWS scoring system and modification of the tool to specific populations in prospective studies is important to quantify deterioration and to define appropriate gradu-ated clinical responses.

The implementation of a pediatric early warning system in this pediatric hematology/oncology unit was successful. PEWS implementation has led to a more than 3-fold increase in days between codes on the hematol-ogy/oncology unit that has been sustainable. PEWS implementation has enhanced multidisciplinary team communication, aided in removing barriers that prevent timely identification and referral of children who are get-ting sicker, and has helped to better ensure the important outcome of each patient receiving the right care in the right location at the right time.

Declaration of Conflicting Interests

The authors declared no conflicts of interest with respect to the authorship and/or publication of this.

Funding

The authors received no financial support for the research and/or authorship of this article.

References

Agency for Healthcare Research and Quality. (2004). Patient safety indicators. Retrieved June 2008, from http://www.qualityindicators.ahrq.gov/psi_overview.htm

Ball, C., Kirkby, M., & Williams, S. (2003). Effect of the critical care outreach team on patient survival to discharge from hos-pital and readmission to critical care: Non-randomized popu-lation based study. British Medical Journal, 327, 1014-1017.

Buist, M. D., Jarmolowski, E., Burton, P., Bernards, S., Waxman, B., & Anderson, J. (1999). Recognizing clinical instability in hospital patients before cardiac arrest or unplanned ICU admission. Medical Journal of Australia, 171, 22-25.

Buist, M. D., Moore, G. E., Bernard, S. A., Waxman, B. P., Anderson, J. N., & Nguyen, T. V. (2002). Effects of a medical emergency team on reduction of incidence of morbidity and mortality from unexpected cardiac arrests in hospitals: Preliminary study. British Medical Journal, 324, 387-390.

Department of Health. (2002). Comprehensive critical care: A review of adult critical care services: London: Author.

Duncan, H., Hutchison, J., & Parshuram, C. S. (2006). The pediatric early warning system score: A severity of illness score to predict urgent medical need in hospitalized chil-dren. Journal of Critical Care, 21, 271-278.

Fiser, R. T., West, N. K., Bush, A. J., Sillos, E. M., Schmidt, J. E., & Tamburro, R. F. (2005). Outcome of severe sepsis in pedi-atric oncology patients. Pediatric Critical Care Medicine, 6, 531-536.

Franklin, C., & Mathew, J. (1994). Developing strategies to pre-vent in-hospital cardiac arrest: Analyzing responses of physi-cians and nurses in the hours before the event. Critical Care Medicine, 22, 244-247.

Gerdes, J. S. (1991). Clinicopathologic approach to the diagnosis of neonatal sepsis. Clinics in Perinatology, 18, 361-381.

Goldhill, D. R., Worthington, L., Mulcahy, A., Tarling, M., & Sumner, A. (1999). The patient-at-risk team: Identifying and managing seriously ill ward patients. Anaesthesia, 54, 853-860.

Gosfield, G., & Reinertsen, J. (2005). The 100,000 lives cam-paign: Crystallizing standards of care for hospitals. Health Affairs, 24, 1560-1570.

Greaves, I., Porter, K., & Ryan, J. (2001). Trauma care manual. London: Manchester Triage Group.

Hallahan, A. R., Shaw, P. J., Rowell, G., O’Connell A., Schell, D., & Gillis, J. (2000). Improved outcome of children with malig-nancies admitted to a pediatric intensive care unit. Critical Care Medicine, 28, 3718-3721.

Han, Y., Carcillo, J. A., & Dragotta, M. (2000). Early rever-sal of shock is associated with improved outcome during inter-facility transport of pediatric septic shock. Pediatric Research, 47, 108A.

Institute for Healthcare Improvement. (2004). 100K lives cam-paign. Retrieved August 2008, from www.ihi.org/IHI/Pro-grams/Campaign

Institute for Healthcare Improvement. (2004). 100,000 lives campaign. Retrieved from http://jama.ama-assn.org/cgi/content/full/295/3/324

Institute for Healthcare Improvement. (2005). 110K lives cam-paign. Retrieved June 2008, from www.ihi.org/IHI/Programs/ Campaign

Institute for Healthcare Improvement. (2009). Frequently asked questions about the 100,000 lives campaign. Retrieved December 24, 2009, from http://ihi.org/IHI/Programs/Cam-paign/FAQsAbout100000LivesCampaign.html

Institute of Medicine. (2004). Keeping patients safe: Trans-forming the work environment of nurses. Washington, DC: National Academy of Sciences.

Joint Commission on Accreditation of Healthcare Organiza-tions. (2009). 2009 National patient safety goals. Retrieved December 24, 2009, from http://www.jointcommission.org/GeneralPublic/NPSG/09_npsgs.htm

Lopez-Herce, J., Garcia, C., Dominguez, P., Carrillo, A., Rodriguez-Nunez, A., Calvo, C., et al. (2004). Character-istics and outcomes of cardio-respiratory arrest in children. Resuscitation, 63, 311-320.

Maningas, P. A., Hime, D. A., & Parker, D. E. (2006). The use of the soterion rapid triage system in children presenting to the emergency department. Journal of Emergency Medicine, 31, 353-359.

Mattie, A. S. (2007). Patient safety; legislation: A look at policy development. Policy, Politics, & Nursing Practice, 8, 251-261.




McGloin, H., Adam, S. K., & Singer, M. (1999). Unex-pected deaths and referrals to intensive care of patients on general wards. Are some cases potentially avoidable? Journal of the Royal College of Physicians London, 33, 255-259.

McQuillan, P., Pilkington, S., Allan, A., Taylor, B., Short, A., Morgan, G., et al. (1998). Confidential inquiry into quality of care before admission to intensive care. British Medical Journal, 316, 1853-1858.

Mendes, A. V., Sapolnik, R., & Mendonca, N. (2007). New guidelines for the clinical management of febrile neutro-penia and sepsis in pediatric oncology patients. Jornal de Pediatria (Rio J), 83(Suppl. 2), S54-S63.

Monaghan, A. (2005, February). Detecting and managing deterioration in children. Paediatric Nursing, 17, 32-35.

Moorhead, S., Johnson, M., Maas, M., & Swanson, E. (2008). Outcome development and significance. In S. Moorhead, M. Johnson, M. Mass, & E. Swanson (Eds.), Nursing out-comes classification (NOC) (4th ed., pp. 3-17). St. Louis, MO: Mosby Elsevier.

Nadkarni, V. M., Larkin, G. L., Peberdy, M. A., Carey, S. M., Kaye, W., Mancini, M. E., et al. (2006). First documented rhythm and clinical outcome from in-hospital cardiac arrest among children and adults. Journal of the American Medical Association, 295, 50-57.

National Cancer Institute. (2006). Surveillance epidemiology and end results. Retrieved December, 24, 2009, from http://seer.cancer.gov/

O’Cathain, A., Webber, E., Nicholl, J., Munro, J., & Knowles, E. (2003). NHS Direct: Consistency of triage outcomes. Emer-gency Medicine Journal, 20, 289-292.

Patel, M. (2008). Triage in children. Trauma, 10, 239-245.Priestley, G., Watson, W., Rashidian, A., Mozley, C., Russell, D.,

Wilson, J., et al. (2004). Introducing critical care outreach: A ward-randomized trial of phased introduction in a general hospital. Intensive Care Medicine, 30, 1398-1404.

Reis, A. G., Nadkarni, V., Perondi, M. B., Grisi, S., & Berg, R. A. (2002). A prospective investigation into the epidemiology of in-hospital pediatric cardio-pulmonary resuscitation using the international Utstein reporting style. Pediatrics, 109, 200-209.

Sharek, P. J., Parast, L. M., Leong, K., Coombs, J., Earnest, K., Sullivan, J., et al. (2007). Effect of a rapid response team on hospital-wide mortality and code rates outside the ICU in a children’s hospital. Journal of the American Medical Asso-ciation, 298, 2267-2274.

Suominen, P., Olkkola, K. T., Voipio, V., Korpela, R., Palo, R., & Rasanen, J. (2000). Utstein style reporting of in-hospital

paediatric cardio-pulmonary resuscitation. Resuscitation, 45, 17-25.

Tamburro, R. (2005). Pediatric cancer patients in clinical trials of sepsis: factors that predispose to sepsis and stratify outcome. Pediatric Critical Care Medicine, 6(Suppl. 3), S87-S91.

Tume, L. (2007). The deterioration of children in ward areas in a specialist children’s hospital. Nursing in Critical Care, 12, 12-19.

Verboon-Maciolek, M. A., Thijsen, S. F., Hemels, M. A., Menses, M., VanLoon, A. M., Rediet, T. G., et al. (2006). Inflammatory mediators for the diagnosis and treatment of sepsis in early infancy. Pediatric Research, 59, 457-461.

Bios

Kathleen M. Demmel, RN, MHA is a nurse who has worked in pediatric hematology/oncology at Cincinnati Children’s Hospital Medical Center for over 6 years. She has served in several roles including the Hematology/Oncology Outpatient Clinic Nursing Director and is currently an Outcome Man-ager for the Hematology/Oncology and Bone Marrow Transplant Divisions focusing on quality improvement and overall patient safety. She received her Masters in Health Care Administration from Xavier University in 1997. Kath-leen also has over 12 years experience in pediatric home health care administration.

Laura Flesch, RN, MSN, CRNP is a certified family nurse practitioner who has worked in pediatric hematology/ oncology-blood & marrow transplant at Cincinnati Chil-dren’s Hospital Medical Center (CCHMC) for more than 10 years. She has served in several roles including nurse practi-tioner (NP) for the inpatient Hematology/Oncology and Blood & Marrow Transplant units; immunology and blood & marrow transplant NP in the Hematology/Oncology Clinic/Day Hospital and is currently the Clinical Director for the Blood & Marrow transplant Program. She received her BSN and MSN from Northern Kentucky University in 1996 and 1999, respectively. Laura also has 4 years experience in the emergency department at CCHMC which is a level I trauma center.

Lucinda Williams, MSN, RN, PNP, NE-BC has worked in pediatric hematology/oncology for 20+ years in Children’s Hospitals in various roles: Nurse practitioner, Clinical Director, Senior Clinical Director. Cindy is currently the Director, Research Nursing at Children’s Hospital Boston. Cindy earned her BSN from Indiana State University in 1975 and her MSN in 1979 from Indiana University.



journal of pediatric oncology nursing 2010 demmel 229 40

Documents